A ROBUST PLS PROCEDURE

A robust partial least squares(PLS)regression algorithm is developed.This is achieved by substitutionof the univariate regression steps in the iterative PLS2 algorithm by a robust alternative.The anglebetween loading vectors from both perturbed and unperturbed solutions is used as a measure ofrobustness.By means of a perturbation study on a structure-activity data set,it is demonstrated thatthe stability of the robust method is superior to standard PLS.     

基于GPU加速的高分辨率实体体素化研究

体素化是面图形学通向体图形学的桥梁,具有广泛且重要的应用。介绍体素化方面的研究进展,分析现有体素化方法在处理高分辨率实体体素化时的不足。提出以分块为基础的高分辨率实体体素化算法:在分块内部,采用基于图形处理器(Graphics Processing Unit,GPU)的切面光栅法对分块表面体素化过程进行加速,采用射线求交方式生成种子并进行块内填充;在分块之间,设计了3方向的种子扩散面及跨块扩散机制,避免因分块而导致的大量几何求交运算,提高了效率。针对高分辨率实体体素化结果数据量大的问题,采用低分辨率表面体素化结果进行数据压缩和索引,节省了数据存储空间。测试结果表明,该文提出的算法不仅能够进行高分辨率实体体素化,而且在GIS、地学建模和CAD等体图形学相关的领域具有重要的应用价值。     

A partition‐based serial algorithm for generating viewshed on massive DEMs

As increasingly large‐scale and higher‐resolution terrain data have become available, for example air‐form and space‐borne sensors, the volume of these datasets reveals scalability problems with existing GIS algorithms. To address this problem, a kind of serial algorithm was developed to generate viewshed on large grid‐based digital elevation models (DEMs). We first divided the whole DEM into rectangular blocks in row and column directions (called block partitioning), then processed these blocks with four axes followed by four sectors sequentially. When processing the particular block, we adopted the ‘reference plane’ algorithm to calculate the visibility of the target point on the block, and adjusted the calculation sequence according to the different spatial relationships between the block and the viewpoint since the viewpoint is not always inside the DEM. By adopting the ‘Reference Plane’ algorithm and using a block partitioning method to segment and load the DEM dynamically, it is possible to generate viewshed efficiently in PC‐based environments. Experiments showed that the divided block should be dynamically loaded whole into computer main memory when partitioning, and the suggested approach retains the accuracy of the reference plane algorithm and has near linear compute complexity.     

Size distribution of urban blocks in the Tokyo Metropolitan Region: estimation by urban block density and road width on the basis of normative plane tessellation

The size distribution of urban blocks is important for the characterisation of urban block patterns and is known to follow several parametric statistical distributions. However, it has not previously been analysed on the basis of a normative plane tessellation and in terms of urban block density and mean road width. In this article, we formulate the size distribution of Voronoi cells using the gamma distribution estimated by urban block density and mean road width. We found that (1) both log-normal and gamma distributions can be good candidates for the size distribution of urban blocks at the scale of a region that consists of regular urban blocks and that has a uniform road width; and (2) the size distribution of urban blocks depends on the balance between pattern and width improvement effects. Based on one study region in Tokyo, if the pattern improvement effect is more prominent than the width improvement effect, the mode of urban block sizes tends to be larger than if it is not. These findings are expected to provide scientific support for urban planning (e.g. land readjustment projects).     

COMMENTS ON THE NIPALS ALGORITHM

The Non-linear lterative Partial Least Squares(NIPALS)algorithm is used in principal componentanalysis to decompose a data matrix into score vectors and eigenvectors(loading vectors)plus a residualmatrix.N1PALS starts with some guessed starting vector.The principal components obtained by NIPALSdepends on the starting vector;the first principal component could not always be computed.Wold hassuggested a starting vector for NIPALS,but we have found that even if this starting vector is used,thefirst principal component cannot be obtained in all cases.The reason why such a situation occurs isexplained by the power method.A simple modification of the original NIPALS procedure to avoid gettingsmaller eigenvalues is presented.     

Variable resolution block kriging using a hierarchical spatial data structure

Abstract

Kriging is an optimal method of spatial interpolation that produces an error for each interpolated value. Block kriging is a form of kriging that computes averaged estimates over blocks (areas or volumes) within the interpolation space. If this space is sampled sparsely, and divided into blocks of a constant size, a variable estimation error is obtained for each block, with blocks near to sample points having smaller errors than blocks farther away. An alternative strategy for sparsely sampled spaces is to vary the sizes of blocks in such away that a block's interpolated value is just sufficiently different from that of an adjacent block given the errors on both blocks. This has the advantage of increasing spatial resolution in many regions, and conversely reducing it in others where maintaining a constant size of block is unjustified (hence achieving data compression). Such a variable subdivision of space can be achieved by regular recursive decomposition using a hierarchical data structure. An implementation of this alternative strategy employing a split-and-merge algorithm operating on a hierarchical data structure is discussed. The technique is illustrated using an oceanographic example involving the interpolation of satellite sea surface temperature data. Consideration is given to the problem of error propagation when combining variable resolution interpolated fields in GIS modelling operations.     

A polygon-based approach for matching OpenStreetMap road networks with regional transit authority data

Matching road networks is an essential step for data enrichment and data quality assessment, among other processes. Conventionally, road networks from two datasets are matched using a line-based approach that checks for the similarity of properties of line segments. In this article, a polygon-based approach is proposed to match the OpenStreetMap road network with authority data. The algorithm first extracts urban blocks that are central elements of urban planning and are represented by polygons surrounded by their surrounding streets, and it then assigns road lines to edges of urban blocks by checking their topologies. In the matching process, polygons of urban blocks are matched in the first step by checking for overlapping areas. In the second step, edges of a matched urban block pair are further matched with each other. Road lines that are assigned to the same matched pair of urban block edges are then matched with each other. The computational cost is substantially reduced because the proposed approach matches polygons instead of road lines, and thus, the process of matching is accelerated. Experiments on Heidelberg and Shanghai datasets show that the proposed approach achieves good and robust matching results, with a precision higher than 96% and a F1-score better than 90%.     

Finite-difference modelling of magnetotelluric fields in two-dimensional anisotropic media

An algorithm for the numerical modelling of magnetotelluric fields in 2-D generally anisotropic block structures is presented. Electrical properties of the individual homogeneous blocks are described by an arbitrary symmetric and positive-definite conductivity tensor. The problem leads to a coupled system of partial differential equations for the strike-parallel components of the electromagnetic field. E _x, and H _x These equations are numerically approximated by the finite-difference (FD) method, making use of the integro-interpolation approach. As the magnetic component H _x, is constant in the non-conductive air, only equations for the electric mode are approximated within the air layer. The system of linear difference equations, resulting from the FD approximation, can be arranged in such a way that its matrix is symmetric and band-limited, and can be solved, for not too large models, by Gaussian elimination. The algorithm is applied to model situations which demonstrate some non-trivial phenomena caused by electrical anisotropy. In particular, the effect of 2-D anisotropy on the relation between magnetotelluric impedances and induction arrows is studied in detail.     

NaBr-RbBr熔盐体系相图

采用偏最小二乘法 (PLS) ,对一价金属卤化物同阴离子二元系固溶体形成规律进行了研究 ,根据研究结果预报表明NaBr-RbBr系可能形成固溶体。并采用差热分析法和目测法重新测定了NaBr-RbBr熔盐体系相图 ,对实验结果进行了热力学评估 ,结果表明认为该体系形成有限固溶体较为合理     

NDVI prediction over Mongolian grassland using GSMaP precipitation data and JRA-25/JCDAS temperature data

An algorithm to predict the NDVI (Normalized Difference Vegetation Index) distribution over Mongolia, which is based on a stepwise multiple linear regression analysis, has been developed using global precipitation data obtained from satellites and global surface air temperature data obtained from the reanalysis data during the period 1998–2005. This algorithm can predict the NDVI value up to 1–3 months in advance for a grid with a spatial resolution of 0.25° × 0.25°.In order to validate the algorithm, the NDVI distribution was predicted for the period from May to November 2006 using 1 to 3-month prediction algorithms. The distributions of the predicted normalized anomalies agreed well with those of the observed normalized anomalies. It was found that these algorithms were effective for arid and semi-arid regions, despite its low accuracy for August and regions with high vegetation activity.     

Identification, characteristics and classification of cryogenic block streams

Cryogenic block streams consist of a stream of rocks superficially resembling a stream deposit but lacking a matrix, usually occurring on a valley or gully floor or on slopes that are less steep than the maximum angle of repose of coarse sediments. They are usually formed on perennially frozen ground, but can also occur as relict landforms. There are three main active kinds forming today, viz., Siberian and Tibetan dynamic rock streams and lag block streams. During their formation, the blocks in the active Siberian and Tibetan dynamic block streams move downslope at up to 1 m/a. They are forming today on the Tibetan Plateau and in the more arid parts of south-central Siberia, although the processes involved in the movement are different. In the case of the Tibetan type, individual blocks slide downslope over the substrate in winter on an icy coating in areas of minimal winter precipitation. The Siberian type develops in areas of 15–80 cm of winter snow cover and an MAAT(mean annual air temperature) of-4 °C to-17 °C. The movement is due to creep of snow and ice and collapse of the blocks downslope during thawing. Lag block streams are formed by meltwater flowing over the surface of sediment consisting primarily of larger blocks with a limited amount of interstitial sediment. The erosion of the matrix is primarily in the spring in areas of higher winter precipitation on 10°–30° slopes. The blocks remain stationary, but the interstitial sediment is washed out by strong seasonal flows of meltwater or rain to form an alluvial fan. The boulders undergo weathering and become more rounded in the process. Lag block streams can also develop without the presence of permafrost in areas with cold climates or glaciers. Block streams also occur as relict deposits in older deposits under various climatic regimes that are unsuitable for their formation today. An example of relict lag block streams with subangular to subrounded blocks occurs in gullies on the forested mountainsides at Felsen in Germany, and is the original "felsenmeer". Similar examples occur near Vitosha Mountain in Bulgaria. The "stone runs" in the Falkland Islands are examples of the more angular relict lag block streams. In both Tasmania and the Falkland Islands, they mask a more complex history, the underlying soils indicating periods of tropical and temperate soil formation resulting from weathering during and since the Tertiary Period. Block streams have also been reported from beneath cold-based glaciers in Sweden, and below till in Canada, and when exhumed, can continue to develop.     

A partial least-squares regression approach to land use studies in the Suzhou-Wuxi-Changzhou region

In several LUCC studies, statistical methods are being used to analyze land use data. A problem using conventional statistical methods in land use analysis is that these methods assume the data to be statistically independent. But in fact, they have the tendency to be dependent, a phenomenon known as multicollinearity, especially in the cases of few observations. In this paper, a Partial Least-Squares (PLS) regression approach is developed to study relationships between land use and its influencing factors through a case study of the Suzhou-Wuxi-Changzhou region in China. Multicollinearity exists in the dataset and the number of variables is high compared to the number of observations. Four PLS factors are selected through a preliminary analysis. The correlation analyses between land use and in-fluencing factors demonstrate the land use character of rural industrialization and urbaniza-tion in the Suzhou-Wuxi-Changzhou region, meanwhile illustrate that the first PLS factor has enough ability to best describe land use patterns quantitatively, and most of the statistical relations derived from it accord with the fact. By the decreasing capacity of the PLS factors, the reliability of model outcome decreases correspondingly.     

偏最小二乘法在苏锡常地区土地利用研究中的应用

In several LUCC studies, statistical methods are being used to analyze land use data. A problem using conventional statistical methods in land use analysis is that these methods assume the data to be statistically independent. But in fact, they have the tendency to be dependent, a phenomenon known as multicollinearity, especially in the cases of few observations. In this paper, a Partial Least-Squares （PLS） regression approach is developed to study relationships between land use and its influencing factors through a case study of the Suzhou-Wuxi-Changzhou region in China. Multicollinearity exists in the dataset and the number of variables is high compared to the number of observations. Four PLS factors are selected through a preliminary analysis. The correlation analyses between land use and influencing factors demonstrate the land use character of rural industrialization and urbanization in the Suzhou-Wuxi-Changzhou region, meanwhile illustrate that the first PLS factor has enough ability to best describe land use patterns quantitatively, and most of the statistical relations derived from it accord with the fact. By the decreasing capacity of the PLS factors, the reliability of model outcome decreases correspondingly.     

Nature and Dynamics of an Active Block Stream, Kunlun Pass, Qinghai Province, People's Republic of China

Active block streams are common on the slopes of mountains on the northern, drier portion of the Qinghai-Xizang (Tibetan) Plateau. Between 1990 and 1995, the authors studied a block stream northeast of the crest of the Kunlun Pass at latitude 35°50’N, longitude 94°05’ E. It occurs on a 31° slope facing southwest at 4800 m altitude and consists of a 15 cm layer of blocks moving downslope over a sandy loam of lacustrine origin. The blocks are derived from both frost shattering of exposed bedrock and by ejection of blocks from the till capping the hill. No water flows in the block stream and its surface is level with the surrounding slope. Mean annual air temperature is –6°C and mean annual precipitation is about 320 mm. The few plants growing between the blocks exhibit elongated stems and/or roots, indicating movement of the upper layers of blocks relative to the underlying materials. Average mean annual downslope movement of the surface blocks ranges up to 95 cm but varies both across the block stream and also along its long axis. The blocks are gradually extending further downslope. Comparison of movement of lines painted on stones in summer and winter shows that most of the movement occurs in winter. The stones usually rotate randomly as they move, probably by sliding on ice. There is no obvious sorting or rounding of the blocks during movement downslope. The deposits produced differ from talus/scree sediments as they have a dip of less than the maximum angle of rest of dry sediment (c. 33°) and also show no sorting downslope. The movement of material takes place predominantly in winter, rather than in summer and the deposits occur in areas of negligible snow cover. Ground temperatures suggest exceptionally rapid temperature changes under the blocks, indicating air exchange in the voids. Mean ground temperatures in the loams beneath the blocks are about 7°C colder than in the adjacent soils. Winter snow covers are noticeably absent, and summer precipitation is often in the form of snow, which soon melts. Permafrost is present beneath the block stream but is absent in the sandy loam soils. The ground is also moister beneath the blocks. It appears that the surface blocks tend to slide downslope on the icy surface of the underlying blocks, perhaps aided by water from melting snow. This and the lack of sorting by clast size clearly differentiates them from talus slopes or avalanche deposits.     

类比合成方法在干旱区内陆河径流量预报中的应用

类比合成算法是一种多维模式搜索法，它具有适用范围广、对资料要求低等优点，可用于单变量及多变量时间序列的延拓预测。通过介绍类比合成算法，并把它应用于塔里木河源流叶尔羌河、和田河年、月径流量预报，其中重点分析了模式长度和合成预报的模式个数等因素对预报结果的影响。通过实测径流资料对预报结果的检验和分析表明，类比合成算法可以较好地挖掘径流序列中隐藏的信息，在中长期水文预报中是一种行之有效的计算方法。     

How block density and typology affect urban vitality: an exploratory analysis in Shenzhen,China

Recent urban transformations in China have led to critical reflections on the low-quality urban expansion in the previous decades and called for the making of vital and lively urban places. To date, limited research has been devoted to empirically testing the relationship between urban design, urban morphology, and urban vitality in Chinese cities. This paper employs new urban data and analytical methods and explores the relationship between urban morphology and urban vitality using regression models. Shenzhen, one of the largest and fastest growing cities in China, is selected as the case study. The regression analysis focuses on two morphological factors, density and typology, while controlling for the accessibility, functional mix, and size of individual blocks. The presence of small catering businesses is used as a proxy for urban vitality. The analysis suggests that both typology and density matter for urban vitality, with typology playing a more important role. More specifically, “block” and “strip” types tend to show significant positive effects on urban vitality. The implications for urban planning and design practices are discussed.     

A TEST OF SIGNIFICANCE FOR PARTIAL LEAST SQUARES REGRESSION

Partial least squares (PLS) regression is a commonly used statistical technique for performingmultivariate calibration, especially in situations where there are more variables than samples. Choosingthe number of factors to include in a model is a decision that all users of PLS must make, but iscomplicated by the large number of empirical tests available. In most instances predictive ability is themost desired property of a PLS model and so interest has centred on making this choice based on aninternal validation process. A popular approach is the calculation of a cross-validated r~2 to gauge howmuch variance in the dependent variable can be explained from leave-one-out predictions. Using MonteCarlo simulations for different sizes of data set, the influence of chance effects on the cross-validationprocess is investigated. The results are presented as tables of critical values which are compared againstthe values of cross-validated r~2 obtained from the user's own data set. This gives a formal test forpredictive ability of a PLS model with a given number of dimensions.     

Optimal spatial allocation of irrigation water under uncertainty using the bilayer nested optimisation algorithm and geospatial technology

The optimal spatial allocation of irrigation water under uncertainty has become a serious concern because of irrigation water shortage and uncertain factors that affect irrigation water allocation. In this study, an optimal multi-objective model for irrigation water allocation under uncertainty is developed to maximise the economic benefit of crops and minimise the operation cost and water deficit of crop irrigation. The original and optimal plantation structure, irrigation mode and soil water content are acquired through geospatial technology. A bilayer nested optimisation (BLNO) algorithm is designed to produce multiple individuals of design vectors using an ant colony neural network algorithm for an outer optimisation. Meanwhile, a continuous adaptive ant colony (CAAC) algorithm is used for inner optimisation to calculate the interval values of the uncertain model. The crop distribution and irrigation mode are obtained to parameterise the planting area and the water demand of each crop and each block in the multi-objective model. This model is then solved and analysed. Compared to the optimal schemes obtained from an inexact two-stage fuzzy-stochastic programming and the CAAC, respectively, BLNO can effectively and efficiently solve the optimal spatial allocation of irrigation water under uncertainty. This method can spatially maximise the economic benefit of crops and minimise the operation cost and water deficit of crop irrigation using lower and upper bound maps whilst visually obtaining the exact crop type, reasonable irrigation method and precise water demand for each block and for the entire irrigated area.     

Earthquake swarms as a long-range precursor to large earthquakes in Turkey

Summary. Turkey has been the location of a series of major earthquakes during this century. This study is an attempt to predict these in hindsight using swarms of weak earthquakes as a long-range precursor as proposed by Keilis-Borok. Some modifications of the swarm identification algorithm are made and statistical measures of success to judge the success of the prediction scheme were introduced. The main measures of success are the percentage of large earthquakes predicted and the percentage of swarms that predicted large earthquakes. The method was applied separately to earthquakes in the North Anatolian Fault Zone and in Western Turkey. The North Anatolian Fault was first considered in its entirety and then in segments. Prediction was attempted in each of these regions with a variety of parameters and the measures of success with confidence levels are computed.
The results obtained for prediction in Turkey are promising. The success of predicting large earthquakes ( M ≥ 7) was generally greater than 60 per cent. The difficulties of this method arise from incomplete catalogues of seismicity and the use of many arbitrary parameters.     

基于自然区块的城市热环境空间分异性研究

通过有效解决建设用地子类划分,实现定量评价城市热环境的空间分异性,对改善城市生态环境、实现城市化的健康发展具有重要的意义和科学价值。论文以广州市为例,参考自然城市的概念,基于5类兴趣点(Point Of Interest,POI)开放数据,结合城市建设用地分类标准,构建5类自然区块;在Landsat 8遥感影像地表温度反演的基础上,计算分析自然区块下地表热场等级分布格局、热场平均值及热环境足迹范围,以对城市热环境空间分异性进行评价。研究表明：① 自然区块的构建,能准确地反映各类POI数据空间分布情况,能够实现对建设用地子类型的划分;② 5类自然区块内部地表热场等级均以高温像元为主,但等级分布具有显著差异。同时,自然区块的热场平均值由高到低的排序为：工业区块>商业服务业区块>交通与道路区块>居住区块>公共管理与服务区块;③ 自然区块形成的高温集聚区,存在热量扩散现象,实际影响范围大于其物理边界,5类自然区块的热环境足迹范围具有分异性。热环境足迹影响范围由大到小排序为：工业区块>商业服务业区块>居住区块>道路与交通区块>公共管理与服务区块。研究结果可为微观尺度上分析城市热环境、改善城市生态环境、实现城市化的健康发展提供科学依据。